Storage unit (su) report cards

ABSTRACT

A computing device includes an interface configured to interface and communicate with a dispersed storage network (DSN), a memory that stores operational instructions, and processing circuitry operably coupled to the interface and to the memory. The processing circuitry is configured to execute the operational instructions to perform various operations and functions. The computing device maintain memory ranking information for a set of storage units (SUs) and receives a read data request. The computing device selects a decode threshold number and/or a read threshold number of SUs to service the read data request based on the memory ranking information. The computing device recovers the data segment and transmits a read data response that is based on the processing the read data request.

CROSS REFERENCE TO RELATED PATENTS

The present U.S. Utility Patent Application claims priority pursuant to35 U.S.C. § 120 as a continuation-in-part (CIP) of U.S. Utility patentapplication Ser. No. 14/986,279, entitled “STORING DATA IN A DISPERSEDSTORAGE NETWORK,” filed Dec. 31, 2015, pending, which claims prioritypursuant to 35 U.S.C. § 119(e) to U.S. Provisional Application No.62/121,667, entitled “SELECTING A STORAGE POOL OF A DISPERSED STORAGENETWORK,” filed Feb. 27, 2015, both of which are hereby incorporatedherein by reference in their entirety and made part of the present U.S.Utility Patent Application for all purposes.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not applicable.

INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC

Not applicable.

BACKGROUND OF THE INVENTION Technical Field of the Invention

This invention relates generally to computer networks and moreparticularly to dispersing error encoded data.

Description of Related Art

Computing devices are known to communicate data, process data, and/orstore data. Such computing devices range from wireless smart phones,laptops, tablets, personal computers (PC), work stations, and video gamedevices, to data centers that support millions of web searches, stocktrades, or on-line purchases every day. In general, a computing deviceincludes a central processing unit (CPU), a memory system, userinput/output interfaces, peripheral device interfaces, and aninterconnecting bus structure.

As is further known, a computer may effectively extend its CPU by using“cloud computing” to perform one or more computing functions (e.g., aservice, an application, an algorithm, an arithmetic logic function,etc.) on behalf of the computer. Further, for large services,applications, and/or functions, cloud computing may be performed bymultiple cloud computing resources in a distributed manner to improvethe response time for completion of the service, application, and/orfunction. For example, Hadoop is an open source software framework thatsupports distributed applications enabling application execution bythousands of computers.

In addition to cloud computing, a computer may use “cloud storage” aspart of its memory system. As is known, cloud storage enables a user,via its computer, to store files, applications, etc. on an Internetstorage system. The Internet storage system may include a RAID(redundant array of independent disks) system and/or a dispersed storagesystem that uses an error correction scheme to encode data for storage.

Prior art data storage systems do not provide means by which theperformance of the components therein is tracked and monitored to assistin the overall operation and performance of the system. The prior artdoes not provide means by which operation of such a system is notadversely affected by degradation and/or failure of the componentstherein.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a schematic block diagram of an embodiment of a dispersed ordistributed storage network (DSN) in accordance with the presentinvention;

FIG. 2 is a schematic block diagram of an embodiment of a computing corein accordance with the present invention;

FIG. 3 is a schematic block diagram of an example of dispersed storageerror encoding of data in accordance with the present invention;

FIG. 4 is a schematic block diagram of a generic example of an errorencoding function in accordance with the present invention;

FIG. 5 is a schematic block diagram of a specific example of an errorencoding function in accordance with the present invention;

FIG. 6 is a schematic block diagram of an example of a slice name of anencoded data slice (EDS) in accordance with the present invention;

FIG. 7 is a schematic block diagram of an example of dispersed storageerror decoding of data in accordance with the present invention;

FIG. 8 is a schematic block diagram of a generic example of an errordecoding function in accordance with the present invention;

FIG. 9 is a schematic block diagram of another embodiment of a dispersedstorage network (DSN) in accordance with the present invention;

FIG. 10 is a flowchart illustrating an example of selecting recoverystorage resources in accordance with the present invention; and

FIG. 11 is a diagram illustrating an embodiment of a method forexecution by one or more computing devices in accordance with thepresent invention.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 is a schematic block diagram of an embodiment of a dispersed, ordistributed, storage network (DSN) 10 that includes a plurality ofcomputing devices 12-16, a managing unit 18, an integrity processingunit 20, and a DSN memory 22. The components of the DSN 10 are coupledto a network 24, which may include one or more wireless and/or wirelined communication systems; one or more non-public intranet systemsand/or public internet systems; and/or one or more local area networks(LAN) and/or wide area networks (WAN).

The DSN memory 22 includes a plurality of storage units 36 that may belocated at geographically different sites (e.g., one in Chicago, one inMilwaukee, etc.), at a common site, or a combination thereof. Forexample, if the DSN memory 22 includes eight storage units 36, eachstorage unit is located at a different site. As another example, if theDSN memory 22 includes eight storage units 36, all eight storage unitsare located at the same site. As yet another example, if the DSN memory22 includes eight storage units 36, a first pair of storage units are ata first common site, a second pair of storage units are at a secondcommon site, a third pair of storage units are at a third common site,and a fourth pair of storage units are at a fourth common site. Notethat a DSN memory 22 may include more or less than eight storage units36. Further note that each storage unit 36 includes a computing core (asshown in FIG. 2, or components thereof) and a plurality of memorydevices for storing dispersed error encoded data.

Each of the computing devices 12-16, the managing unit 18, and theintegrity processing unit 20 include a computing core 26, which includesnetwork interfaces 30-33. Computing devices 12-16 may each be a portablecomputing device and/or a fixed computing device. A portable computingdevice may be a social networking device, a gaming device, a cell phone,a smart phone, a digital assistant, a digital music player, a digitalvideo player, a laptop computer, a handheld computer, a tablet, a videogame controller, and/or any other portable device that includes acomputing core. A fixed computing device may be a computer (PC), acomputer server, a cable set-top box, a satellite receiver, a televisionset, a printer, a fax machine, home entertainment equipment, a videogame console, and/or any type of home or office computing equipment.Note that each of the managing unit 18 and the integrity processing unit20 may be separate computing devices, may be a common computing device,and/or may be integrated into one or more of the computing devices 12-16and/or into one or more of the storage units 36.

Each interface 30, 32, and 33 includes software and hardware to supportone or more communication links via the network 24 indirectly and/ordirectly. For example, interface 30 supports a communication link (e.g.,wired, wireless, direct, via a LAN, via the network 24, etc.) betweencomputing devices 14 and 16. As another example, interface 32 supportscommunication links (e.g., a wired connection, a wireless connection, aLAN connection, and/or any other type of connection to/from the network24) between computing devices 12 & 16 and the DSN memory 22. As yetanother example, interface 33 supports a communication link for each ofthe managing unit 18 and the integrity processing unit 20 to the network24.

Computing devices 12 and 16 include a dispersed storage (DS) clientmodule 34, which enables the computing device to dispersed storage errorencode and decode data as subsequently described with reference to oneor more of FIGS. 3-8. In this example embodiment, computing device 16functions as a dispersed storage processing agent for computing device14. In this role, computing device 16 dispersed storage error encodesand decodes data on behalf of computing device 14. With the use ofdispersed storage error encoding and decoding, the DSN 10 is tolerant ofa significant number of storage unit failures (the number of failures isbased on parameters of the dispersed storage error encoding function)without loss of data and without the need for a redundant or backupcopies of the data. Further, the DSN 10 stores data for an indefiniteperiod of time without data loss and in a secure manner (e.g., thesystem is very resistant to unauthorized attempts at accessing thedata).

In operation, the managing unit 18 performs DS management services. Forexample, the managing unit 18 establishes distributed data storageparameters (e.g., vault creation, distributed storage parameters,security parameters, billing information, user profile information,etc.) for computing devices 12-14 individually or as part of a group ofuser devices. As a specific example, the managing unit 18 coordinatescreation of a vault (e.g., a virtual memory block associated with aportion of an overall namespace of the DSN) within the DSN memory 22 fora user device, a group of devices, or for public access and establishesper vault dispersed storage (DS) error encoding parameters for a vault.The managing unit 18 facilitates storage of DS error encoding parametersfor each vault by updating registry information of the DSN 10, where theregistry information may be stored in the DSN memory 22, a computingdevice 12-16, the managing unit 18, and/or the integrity processing unit20.

The DSN managing unit 18 creates and stores user profile information(e.g., an access control list (ACL)) in local memory and/or withinmemory of the DSN module 22. The user profile information includesauthentication information, permissions, and/or the security parameters.The security parameters may include encryption/decryption scheme, one ormore encryption keys, key generation scheme, and/or dataencoding/decoding scheme.

The DSN managing unit 18 creates billing information for a particularuser, a user group, a vault access, public vault access, etc. Forinstance, the DSN managing unit 18 tracks the number of times a useraccesses a non-public vault and/or public vaults, which can be used togenerate a per-access billing information. In another instance, the DSNmanaging unit 18 tracks the amount of data stored and/or retrieved by auser device and/or a user group, which can be used to generate aper-data-amount billing information.

As another example, the managing unit 18 performs network operations,network administration, and/or network maintenance. Network operationsincludes authenticating user data allocation requests (e.g., read and/orwrite requests), managing creation of vaults, establishingauthentication credentials for user devices, adding/deleting components(e.g., user devices, storage units, and/or computing devices with a DSclient module 34) to/from the DSN 10, and/or establishing authenticationcredentials for the storage units 36. Network administration includesmonitoring devices and/or units for failures, maintaining vaultinformation, determining device and/or unit activation status,determining device and/or unit loading, and/or determining any othersystem level operation that affects the performance level of the DSN 10.Network maintenance includes facilitating replacing, upgrading,repairing, and/or expanding a device and/or unit of the DSN 10.

The integrity processing unit 20 performs rebuilding of ‘bad’ or missingencoded data slices. At a high level, the integrity processing unit 20performs rebuilding by periodically attempting to retrieve/list encodeddata slices, and/or slice names of the encoded data slices, from the DSNmemory 22. For retrieved encoded slices, they are checked for errors dueto data corruption, outdated version, etc. If a slice includes an error,it is flagged as a ‘bad’ slice. For encoded data slices that were notreceived and/or not listed, they are flagged as missing slices. Badand/or missing slices are subsequently rebuilt using other retrievedencoded data slices that are deemed to be good slices to produce rebuiltslices. The rebuilt slices are stored in the DSN memory 22.

FIG. 2 is a schematic block diagram of an embodiment of a computing core26 that includes a processing module 50, a memory controller 52, mainmemory 54, a video graphics processing unit 55, an input/output (IO)controller 56, a peripheral component interconnect (PCI) interface 58,an IO interface module 60, at least one IO device interface module 62, aread only memory (ROM) basic input output system (BIOS) 64, and one ormore memory interface modules. The one or more memory interfacemodule(s) includes one or more of a universal serial bus (USB) interfacemodule 66, a host bus adapter (HBA) interface module 68, a networkinterface module 70, a flash interface module 72, a hard drive interfacemodule 74, and a DSN interface module 76.

The DSN interface module 76 functions to mimic a conventional operatingsystem (OS) file system interface (e.g., network file system (NFS),flash file system (FFS), disk file system (DFS), file transfer protocol(FTP), web-based distributed authoring and versioning (WebDAV), etc.)and/or a block memory interface (e.g., small computer system interface(SCSI), internet small computer system interface (iSCSI), etc.). The DSNinterface module 76 and/or the network interface module 70 may functionas one or more of the interface 30-33 of FIG. 1. Note that the IO deviceinterface module 62 and/or the memory interface modules 66-76 may becollectively or individually referred to as IO ports.

FIG. 3 is a schematic block diagram of an example of dispersed storageerror encoding of data. When a computing device 12 or 16 has data tostore it disperse storage error encodes the data in accordance with adispersed storage error encoding process based on dispersed storageerror encoding parameters. The dispersed storage error encodingparameters include an encoding function (e.g., information dispersalalgorithm, Reed-Solomon, Cauchy Reed-Solomon, systematic encoding,non-systematic encoding, on-line codes, etc.), a data segmentingprotocol (e.g., data segment size, fixed, variable, etc.), and per datasegment encoding values. The per data segment encoding values include atotal, or pillar width, number (T) of encoded data slices per encodingof a data segment i.e., in a set of encoded data slices); a decodethreshold number (D) of encoded data slices of a set of encoded dataslices that are needed to recover the data segment; a read thresholdnumber (R) of encoded data slices to indicate a number of encoded dataslices per set to be read from storage for decoding of the data segment;and/or a write threshold number (W) to indicate a number of encoded dataslices per set that must be accurately stored before the encoded datasegment is deemed to have been properly stored. The dispersed storageerror encoding parameters may further include slicing information (e.g.,the number of encoded data slices that will be created for each datasegment) and/or slice security information (e.g., per encoded data sliceencryption, compression, integrity checksum, etc.).

In the present example, Cauchy Reed-Solomon has been selected as theencoding function (a generic example is shown in FIG. 4 and a specificexample is shown in FIG. 5); the data segmenting protocol is to dividethe data object into fixed sized data segments; and the per data segmentencoding values include: a pillar width of 5, a decode threshold of 3, aread threshold of 4, and a write threshold of 4. In accordance with thedata segmenting protocol, the computing device 12 or 16 divides the data(e.g., a file (e.g., text, video, audio, etc.), a data object, or otherdata arrangement) into a plurality of fixed sized data segments (e.g., 1through Y of a fixed size in range of Kilo-bytes to Tera-bytes or more).The number of data segments created is dependent of the size of the dataand the data segmenting protocol.

The computing device 12 or 16 then disperse storage error encodes a datasegment using the selected encoding function (e.g., Cauchy Reed-Solomon)to produce a set of encoded data slices. FIG. 4 illustrates a genericCauchy Reed-Solomon encoding function, which includes an encoding matrix(EM), a data matrix (DM), and a coded matrix (CM). The size of theencoding matrix (EM) is dependent on the pillar width number (T) and thedecode threshold number (D) of selected per data segment encodingvalues. To produce the data matrix (DM), the data segment is dividedinto a plurality of data blocks and the data blocks are arranged into Dnumber of rows with Z data blocks per row. Note that Z is a function ofthe number of data blocks created from the data segment and the decodethreshold number (D). The coded matrix is produced by matrix multiplyingthe data matrix by the encoding matrix.

FIG. 5 illustrates a specific example of Cauchy Reed-Solomon encodingwith a pillar number (T) of five and decode threshold number of three.In this example, a first data segment is divided into twelve data blocks(D1-D12). The coded matrix includes five rows of coded data blocks,where the first row of X11-X14 corresponds to a first encoded data slice(EDS 1_1), the second row of X21-X24 corresponds to a second encodeddata slice (EDS 2_1), the third row of X31-X34 corresponds to a thirdencoded data slice (EDS 3_1), the fourth row of X41-X44 corresponds to afourth encoded data slice (EDS 4_1), and the fifth row of X51-X54corresponds to a fifth encoded data slice (EDS 5_1). Note that thesecond number of the EDS designation corresponds to the data segmentnumber.

Returning to the discussion of FIG. 3, the computing device also createsa slice name (SN) for each encoded data slice (EDS) in the set ofencoded data slices. A typical format for a slice name 60 is shown inFIG. 6. As shown, the slice name (SN) 60 includes a pillar number of theencoded data slice (e.g., one of 1-T), a data segment number (e.g., oneof 1-Y), a vault identifier (ID), a data object identifier (ID), and mayfurther include revision level information of the encoded data slices.The slice name functions as, at least part of, a DSN address for theencoded data slice for storage and retrieval from the DSN memory 22.

As a result of encoding, the computing device 12 or 16 produces aplurality of sets of encoded data slices, which are provided with theirrespective slice names to the storage units for storage. As shown, thefirst set of encoded data slices includes EDS 1_1 through EDS 5_1 andthe first set of slice names includes SN 1_1 through SN 5_1 and the lastset of encoded data slices includes EDS 1_Y through EDS 5_Y and the lastset of slice names includes SN 1_Y through SN 5_Y.

FIG. 7 is a schematic block diagram of an example of dispersed storageerror decoding of a data object that was dispersed storage error encodedand stored in the example of FIG. 4. In this example, the computingdevice 12 or 16 retrieves from the storage units at least the decodethreshold number of encoded data slices per data segment. As a specificexample, the computing device retrieves a read threshold number ofencoded data slices.

To recover a data segment from a decode threshold number of encoded dataslices, the computing device uses a decoding function as shown in FIG.8. As shown, the decoding function is essentially an inverse of theencoding function of FIG. 4. The coded matrix includes a decodethreshold number of rows (e.g., three in this example) and the decodingmatrix in an inversion of the encoding matrix that includes thecorresponding rows of the coded matrix. For example, if the coded matrixincludes rows 1, 2, and 4, the encoding matrix is reduced to rows 1, 2,and 4, and then inverted to produce the decoding matrix.

In some examples, note that dispersed or distributed storage network(DSN) memory includes one or more of a plurality of storage units (SUs)such as SUs 36 (e.g., that may alternatively be referred to adistributed storage and/or task network (DSTN) module that includes aplurality of distributed storage and/or task (DST) execution units 36that may be located at geographically different sites (e.g., one inChicago, one in Milwaukee, etc.). Each of the SUs (e.g., alternativelyreferred to as DST execution units in some examples) is operable tostore dispersed error encoded data and/or to execute, in a distributedmanner, one or more tasks on data. The tasks may be a simple function(e.g., a mathematical function, a logic function, an identify function,a find function, a search engine function, a replace function, etc.), acomplex function (e.g., compression, human and/or computer languagetranslation, text-to-voice conversion, voice-to-text conversion, etc.),multiple simple and/or complex functions, one or more algorithms, one ormore applications, etc.

FIG. 9 is a schematic block diagram of another embodiment of a dispersedstorage network (DSN) in accordance with the present invention. Thisdiagram includes a schematic block diagram of another embodiment of adispersed storage network (DSN) that includes the computing device 16 ofFIG. 1, the network 24 of FIG. 1, and a set of storage units (SUs) 1−n.The computing device 16 includes the DS client module 34 of FIG. 1 and amemory.

The DSN functions to select recovery storage resources for recoveringdata from the set of SUs, where the data was dispersed storage errorencoded to produce a plurality of sets of encoded data slices that werestored in the set of SUs. In an example of operation of the selecting ofthe recovery storage resources, the DS client module 34, when issuing aread slice request (e.g., read slice requests 930) to the set of SUs,receives read slice responses (e.g., read slice responses 940) from atleast some of the SUs. For example, the DS client module 34 receives aread data request 910, generates a set of read slice requests, sends,via the network 24, the set of read slice requests 1−n to the set ofSUs, and receives the read slice responses 940 from at least some of theSUs.

Having received the read slice responses 940, the DS client module 34maintains memory ranking information based on the received read sliceresponses 940. As a specific example, for each read slice request to acorresponding SU, the DS client module 34 updates a read ranking numberfor the SU, where the read ranking number is maintained as a number ofreceived slices from the SU that were successfully utilized to decodedata divided by a total number of corresponding read requests issued tothe SU. Having updated the read ranking number, the DS client module 34updates the memory ranking information stored in the memory 88 with theupdated read ranking numbers.

Having maintained in the memory ranking information, the DS clientmodule 34 receives a read data request 910 to recover data from the setof SUs. Having received the read data request 910, the DS client module34 selects a read threshold number of SUs of the set of SUs based on thememory ranking information for the set of SUs. The selecting includesone or more of identifying a read threshold number of SUs associatedwith highest read ranking numbers and identifying a read thresholdnumber of SUs associated with read ranking numbers greater than aminimum ranking threshold level.

Having selected the read threshold number of SUs, the DS client module34 recovers the data from the selected read threshold number of SUs. Asan example of the recovering, the DS client module 34 issues, via thenetwork 24, read slice requests 930 to the selected read thresholdnumber of SUs, receives read slice responses 940, and for each set ofencoded data slices, dispersed storage error decodes a decode thresholdnumber of received encoded data slices to reproduce a data segment, andaggregates a plurality of recovered data segments to produce recovereddata. Having recovered the data, the DS client module 34 outputs a readdata response 920 that includes the recovered data.

In an example of operation and implementation, a computing deviceincludes an interface configured to interface and communicate with adispersed or distributed storage network (DSN), a memory that storesoperational instructions, and a processing module, processor, and/orprocessing circuitry operably coupled to the interface and memory. Theprocessing module, processor, and/or processing circuitry is configuredto execute the operational instructions to perform various operations,functions, etc. In some examples, the processing module, processor,and/or processing circuitry, when operable within the computing devicebased on the operational instructions, is configured to perform variousoperations, functions, etc. In certain examples, the processing module,processor, and/or processing circuitry, when operable within thecomputing device is configured to perform one or more functions that mayinclude generation of one or more signals, processing of one or moresignals, receiving of one or more signals, transmission of one or moresignals, interpreting of one or more signals, etc. and/or any otheroperations as described herein and/or their equivalents.

In an example of operation and implementation, a computing device (e.g.,computing device 16 of FIG. 1, FIG. 9, and/or any other diagram,example, embodiment, equivalent, etc. as described herein) is configuredto maintain memory ranking information for a set of storage units (SUs)within the DSN based on data access operations associated therewith.Note that a data object is segmented into a plurality of data segments.Also, a data segment of the plurality of data segments is dispersederror encoded in accordance with dispersed error encoding parameters toproduce a set of encoded data slices (EDSs) that are distributedlystored in the set of SUs within the DSN. A decode threshold number ofEDSs are needed to recover the data segment, and a read threshold numberof EDSs provides for reconstruction of the data segment.

The computing device is also configured to receive (e.g., from anothercomputing device) a read data request. The computing device is alsoconfigured to select a decode threshold number of SUs and/or a readthreshold number of SUs of the set of SUs to service the read datarequest based on the memory ranking information for the set of SUs. Thecomputing device is also configured to recover the data segment from thedecode threshold number of SUs and/or the read threshold number of SUsof the set of SUs in accordance with processing the read data request.The computing device is also configured to transmit (e.g., to the othercomputing device) a read data response that is based on the processingthe read data request.

In some examples, the computing device is also configured to maintainthe memory ranking information for the set of SUs within the DSN basedon updating a read ranking number corresponding to a SU of the set ofSUs based on a number of EDSs of the set of EDSs that are received fromthe SU of the set of SUs that are successfully used to recover the datasegment divided by a total number of corresponding read requests issuedto the SU of the set of SUs.

In even other examples, the computing device is also configured toselect the decode threshold number of SUs and/or the read thresholdnumber of SUs of the set of SUs to service the read data request basedon the memory ranking information for the set of SUs based onidentifying the read threshold number of SUs as being associated withhighest read ranking numbers and identifying the read threshold numberof SUs as being associated with read ranking numbers greater than aminimum ranking threshold level.

In yet other examples, the computing device is also configured torecover the data segment from the decode threshold number of SUs and/orthe read threshold number of SUs of the set of SUs in accordance withprocessing the read data request including to issue a read slice requestto the decode threshold number of SUs and/or the read threshold numberof SUs of the set of SUs, dispersed error decode the decode thresholdnumber of EDSs and/or the read threshold number of EDSs to reproduce thedata segment, and aggregate the data segment with at least one otherdata segment to reproduce the data object.

In some examples, with respect to a data object, the data object issegmented into a plurality of data segments, and a data segment of theplurality of data segments is dispersed error encoded in accordance withdispersed error encoding parameters to produce a set of encoded dataslices (EDSs) (e.g., in some instances, the set of EDSs aredistributedly stored in a plurality of storage units (SUs) within theDSN). In some examples, the set of EDSs is of pillar width. Also, withrespect to certain implementations, note that the decode thresholdnumber of EDSs are needed to recover the data segment, and a readthreshold number of EDSs provides for reconstruction of the datasegment. Also, a write threshold number of EDSs provides for asuccessful transfer of the set of EDSs from a first at least onelocation in the DSN to a second at least one location in the DSN. Theset of EDSs is of pillar width and includes a pillar number of EDSs.Also, in some examples, each of the decode threshold, the readthreshold, and the write threshold is less than the pillar number. Also,in some particular examples, the write threshold number is greater thanor equal to the read threshold number that is greater than or equal tothe decode threshold number.

Note that the computing device as described herein may be located at afirst premises that is remotely located from a second premisesassociated with at least one other SU, dispersed storage (DS) unit,computing device, at least one SU of a plurality of SUs within the DSN(e.g., such as a plurality of SUs that are implemented to storedistributedly a set of EDSs), etc. In addition, note that such acomputing device as described herein may be implemented as any of anumber of different devices including a managing unit that is remotelylocated from another SU, DS unit, computing device, etc. within the DSNand/or other device within the DSN, an integrity processing unit that isremotely located from another computing device and/or other devicewithin the DSN, a scheduling unit that is remotely located from anothercomputing device and/or SU within the DSN, and/or other device. Also,note that such a computing device as described herein may be of any of avariety of types of devices as described herein and/or their equivalentsincluding a DS unit and/or SU included within any group and/or set of DSunits and/or SUs within the DSN, a wireless smart phone, a laptop, atablet, a personal computers (PC), a work station, and/or a video gamedevice, and/or any type of computing device or communication device.Also, note also that the DSN may be implemented to include and/or bebased on any of a number of different types of communication systemsincluding a wireless communication system, a wire lined communicationsystem, a non-public intranet system, a public internet system, a localarea network (LAN), and/or a wide area network (WAN). Also, in someexamples, any device configured to support communications within such aDSN may be also be configured to and/or specifically implemented tosupport communications within a satellite communication system, awireless communication system, a wired communication system, afiber-optic communication system, and/or a mobile communication system(and/or any other type of communication system implemented using anytype of communication medium or media).

FIG. 10 is a flowchart illustrating an example of selecting recoverystorage resources in accordance with the present invention. This diagramincludes a flowchart illustrating an example of selecting recoverystorage resources. The method 1000 begins or continues at a step 1010where a processing module (e.g., of a distributed storage (DS) clientmodule and/or computing device) maintains memory ranking information fora set of storage units based on historical utilization of receivedencoded data slices from the set of storage units. For example, theprocessing module issues read slice requests to the set of storageunits, receives read slice responses from at least some of the storageunits, utilizes encoded data slices extracted from the received readslice responses, updates the memory rink information by determining, foreach storage unit, a read ranking number. The determining of the readranking number includes performing a mathematical function to normalizea number of successfully utilized encoded data slices divided by acorresponding number of read slice requests issued to the correspondingstorage unit.

The method 1000 continues at the step 1020 where the processing modulereceives a read data request to recover data from the set of storageunits. The read data request includes an identifier of the data, wherethe data was dispersed storage error encoded to produce a plurality ofsets of encoded data slices for storage in the set of storage units.

The method 1000 continues at the step 1030 where the processing moduleselects a read threshold number of storage units of the set of storageunits based on the memory ranking information. For example, theprocessing module identifies a read threshold number of storage unitswith highest read ranking numbers. As another example, the processingmodule identifies a read threshold number of storage units associatedwith read ranking numbers greater than a minimum ranking thresholdlevel.

The method 1000 continues at the step 1040 where the processing modulerecovers the data from the selected storage units. For example, theprocessing module issues read slice requests to the selected readthreshold number of storage units, receives encoded data slices, and foreach set of encoded data slices, dispersed storage error decodes adecode threshold number of received encoded data slices to produce arecovered data segment, updates historical records for successfullyutilization of each encoded data slice, and aggregates a plurality ofrecovered data segments to produce recovered data.

The method 1000 continues at the step 1050 where the processing moduleoutputs a read data response to a requesting entity. The outputtingincludes generating the read data response to include one or more of therecovered data and the identifier of the data and sending the read dataresponse to the requesting entity.

FIG. 11 is a diagram illustrating an embodiment of a method 1100 forexecution by one or more computing devices in accordance with thepresent invention. The method 1100 operates in step 1110 by maintainmemory ranking information for a set of storage units (SUs) within adispersed or distributed storage network (DSN) based on data accessoperations associated therewith. Note that a data object is segmentedinto a plurality of data segments, wherein a data segment of theplurality of data segments is dispersed error encoded in accordance withdispersed error encoding parameters to produce a set of encoded dataslices (EDSs) that are distributedly stored in the set of SUs within theDSN. Also, a decode threshold number of EDSs are needed to recover thedata segment, and a read threshold number of EDSs provides forreconstruction of the data segment.

The method 1100 then continues in step 1120 by receiving (e.g., via aninterface of the computing device that is configured to interface andcommunicate with a dispersed or distributed storage network (DSN) andfrom another computing device) a read data request. The method 1100operates in step 1130 by selecting a decode threshold number of SUsand/or a read threshold number of SUs of the set of SUs to service theread data request based on the memory ranking information for the set ofSUs. The method 1100 then continues in step 1140 by recovering the datasegment from the decode threshold number of SUs and/or the readthreshold number of SUs of the set of SUs in accordance with processingthe read data request. The method 1100 then operates in step 1150 bytransmitting (e.g., via the interface and to the other computing device)a read data response that is based on the processing the read datarequest.

This disclosure presents, among other things, various novel solutionsthat provides for storage unit (SU) report cards. There are many mannersin which a storage unit (SU) can respond in a manner that is less thanideal, such as responding with corrupted slice data, responding with anold revision, responding with extraneous revision(s), responding with norevision, responding with an error, or responding after a threshold ofother SUs have already responded. One statistic which embodies all ofthese factors at once is whether or not a slice from that store was usedin a successful IDA decode operation. If the store did not return avalid slice, of a proper revision, in a timely manner, then it's slicewill not be used in a decode operation, if however, it does return avalid slice, of the correct revision, and before the T+1 slowest storereturns a valid slice, then it will be used. Therefore, a useful measureof the utility of a SU to a particular computing device is the number oftimes a slice from that SU is used in a successful decode operation.Since some SUs may be preferentially selected to be read from (e.g.,ReadRanking), to normalize this statistic it may be divided by thenumber of read requests issued to that store. This results in a valuefrom 0 to 1, representing the probability that if the SU is issued aread request, what the historical rate of its response containing andbeing used towards the decoding of the data source. This value may beused directly to guide the Read Ranking algorithm, to determine how manySUs ought to be read from, and perhaps even as a “health indicator” ofSUs (if the computing device reports this number to a “gradingaggregator”). When a SU has a particularly low value, it may indicate aperformance problem, a lack of data health, or other similar problems tobe addressed. To bias the report card towards more recent results (as ismore important for adaptive strategies, an exponential moving average orsimilar weighted ranking may be computed as follows: for some weightingbias between 0 and 1 W, compute:

new_score=(old_score*W)+(latest_result*(1−W))

where latest_result=1 if the SU was used successfully in a sliceoperation, and 0 if a read was issued which did not result in asuccessful slice decode operation.

It is noted that terminologies as may be used herein such as bit stream,stream, signal sequence, etc. (or their equivalents) have been usedinterchangeably to describe digital information whose contentcorresponds to any of a number of desired types (e.g., data, video,speech, audio, etc. any of which may generally be referred to as‘data’).

As may be used herein, the terms “substantially” and “approximately”provides an industry-accepted tolerance for its corresponding termand/or relativity between items. Such an industry-accepted toleranceranges from less than one percent to fifty percent and corresponds to,but is not limited to, component values, integrated circuit processvariations, temperature variations, rise and fall times, and/or thermalnoise. Such relativity between items ranges from a difference of a fewpercent to magnitude differences. As may also be used herein, theterm(s) “configured to”, “operably coupled to”, “coupled to”, and/or“coupling” includes direct coupling between items and/or indirectcoupling between items via an intervening item (e.g., an item includes,but is not limited to, a component, an element, a circuit, and/or amodule) where, for an example of indirect coupling, the intervening itemdoes not modify the information of a signal but may adjust its currentlevel, voltage level, and/or power level. As may further be used herein,inferred coupling (i.e., where one element is coupled to another elementby inference) includes direct and indirect coupling between two items inthe same manner as “coupled to”. As may even further be used herein, theterm “configured to”, “operable to”, “coupled to”, or “operably coupledto” indicates that an item includes one or more of power connections,input(s), output(s), etc., to perform, when activated, one or more itscorresponding functions and may further include inferred coupling to oneor more other items. As may still further be used herein, the term“associated with”, includes direct and/or indirect coupling of separateitems and/or one item being embedded within another item.

As may be used herein, the term “compares favorably”, indicates that acomparison between two or more items, signals, etc., provides a desiredrelationship. For example, when the desired relationship is that signal1 has a greater magnitude than signal 2, a favorable comparison may beachieved when the magnitude of signal 1 is greater than that of signal 2or when the magnitude of signal 2 is less than that of signal 1. As maybe used herein, the term “compares unfavorably”, indicates that acomparison between two or more items, signals, etc., fails to providethe desired relationship.

As may also be used herein, the terms “processing module”, “processingcircuit”, “processor”, and/or “processing unit” may be a singleprocessing device or a plurality of processing devices. Such aprocessing device may be a microprocessor, micro-controller, digitalsignal processor, microcomputer, central processing unit, fieldprogrammable gate array, programmable logic device, state machine, logiccircuitry, analog circuitry, digital circuitry, and/or any device thatmanipulates signals (analog and/or digital) based on hard coding of thecircuitry and/or operational instructions. The processing module,module, processing circuit, and/or processing unit may be, or furtherinclude, memory and/or an integrated memory element, which may be asingle memory device, a plurality of memory devices, and/or embeddedcircuitry of another processing module, module, processing circuit,and/or processing unit. Such a memory device may be a read-only memory,random access memory, volatile memory, non-volatile memory, staticmemory, dynamic memory, flash memory, cache memory, and/or any devicethat stores digital information. Note that if the processing module,module, processing circuit, and/or processing unit includes more thanone processing device, the processing devices may be centrally located(e.g., directly coupled together via a wired and/or wireless busstructure) or may be distributedly located (e.g., cloud computing viaindirect coupling via a local area network and/or a wide area network).Further note that if the processing module, module, processing circuit,and/or processing unit implements one or more of its functions via astate machine, analog circuitry, digital circuitry, and/or logiccircuitry, the memory and/or memory element storing the correspondingoperational instructions may be embedded within, or external to, thecircuitry comprising the state machine, analog circuitry, digitalcircuitry, and/or logic circuitry. Still further note that, the memoryelement may store, and the processing module, module, processingcircuit, and/or processing unit executes, hard coded and/or operationalinstructions corresponding to at least some of the steps and/orfunctions illustrated in one or more of the figures. Such a memorydevice or memory element can be included in an article of manufacture.

One or more embodiments have been described above with the aid of methodsteps illustrating the performance of specified functions andrelationships thereof. The boundaries and sequence of these functionalbuilding blocks and method steps have been arbitrarily defined hereinfor convenience of description. Alternate boundaries and sequences canbe defined so long as the specified functions and relationships areappropriately performed. Any such alternate boundaries or sequences arethus within the scope and spirit of the claims. Further, the boundariesof these functional building blocks have been arbitrarily defined forconvenience of description. Alternate boundaries could be defined aslong as the certain significant functions are appropriately performed.Similarly, flow diagram blocks may also have been arbitrarily definedherein to illustrate certain significant functionality.

To the extent used, the flow diagram block boundaries and sequence couldhave been defined otherwise and still perform the certain significantfunctionality. Such alternate definitions of both functional buildingblocks and flow diagram blocks and sequences are thus within the scopeand spirit of the claims. One of average skill in the art will alsorecognize that the functional building blocks, and other illustrativeblocks, modules and components herein, can be implemented as illustratedor by discrete components, application specific integrated circuits,processors executing appropriate software and the like or anycombination thereof.

In addition, a flow diagram may include a “start” and/or “continue”indication. The “start” and “continue” indications reflect that thesteps presented can optionally be incorporated in or otherwise used inconjunction with other routines. In this context, “start” indicates thebeginning of the first step presented and may be preceded by otheractivities not specifically shown. Further, the “continue” indicationreflects that the steps presented may be performed multiple times and/ormay be succeeded by other activities not specifically shown. Further,while a flow diagram indicates a particular ordering of steps, otherorderings are likewise possible provided that the principles ofcausality are maintained.

The one or more embodiments are used herein to illustrate one or moreaspects, one or more features, one or more concepts, and/or one or moreexamples. A physical embodiment of an apparatus, an article ofmanufacture, a machine, and/or of a process may include one or more ofthe aspects, features, concepts, examples, etc. described with referenceto one or more of the embodiments discussed herein. Further, from figureto figure, the embodiments may incorporate the same or similarly namedfunctions, steps, modules, etc. that may use the same or differentreference numbers and, as such, the functions, steps, modules, etc. maybe the same or similar functions, steps, modules, etc. or differentones.

Unless specifically stated to the contra, signals to, from, and/orbetween elements in a figure of any of the figures presented herein maybe analog or digital, continuous time or discrete time, and single-endedor differential. For instance, if a signal path is shown as asingle-ended path, it also represents a differential signal path.Similarly, if a signal path is shown as a differential path, it alsorepresents a single-ended signal path. While one or more particulararchitectures are described herein, other architectures can likewise beimplemented that use one or more data buses not expressly shown, directconnectivity between elements, and/or indirect coupling between otherelements as recognized by one of average skill in the art.

The term “module” is used in the description of one or more of theembodiments. A module implements one or more functions via a device suchas a processor or other processing device or other hardware that mayinclude or operate in association with a memory that stores operationalinstructions. A module may operate independently and/or in conjunctionwith software and/or firmware. As also used herein, a module may containone or more sub-modules, each of which may be one or more modules.

As may further be used herein, a computer readable memory includes oneor more memory elements. A memory element may be a separate memorydevice, multiple memory devices, or a set of memory locations within amemory device. Such a memory device may be a read-only memory, randomaccess memory, volatile memory, non-volatile memory, static memory,dynamic memory, flash memory, cache memory, and/or any device thatstores digital information. The memory device may be in a form a solidstate memory, a hard drive memory, cloud memory, thumb drive, servermemory, computing device memory, and/or other physical medium forstoring digital information.

While particular combinations of various functions and features of theone or more embodiments have been expressly described herein, othercombinations of these features and functions are likewise possible. Thepresent disclosure is not limited by the particular examples disclosedherein and expressly incorporates these other combinations.

What is claimed is:
 1. A computing device comprising: an interfaceconfigured to interface and communicate with a dispersed or distributedstorage network (DSN); memory that stores operational instructions; andprocessing circuitry operably coupled to the interface and to thememory, wherein the processing circuitry is configured to execute theoperational instructions to: maintain memory ranking information for aset of storage units (SUs) within the DSN based on data accessoperations associated therewith, wherein a data object is segmented intoa plurality of data segments, wherein a data segment of the plurality ofdata segments is dispersed error encoded in accordance with dispersederror encoding parameters to produce a set of encoded data slices (EDSs)that are distributedly stored in the set of SUs within the DSN, whereina decode threshold number of EDSs are needed to recover the datasegment, wherein a read threshold number of EDSs provides forreconstruction of the data segment; receive, from another computingdevice, a read data request; select at least one of a decode thresholdnumber of SUs or a read threshold number of SUs of the set of SUs toservice the read data request based on the memory ranking informationfor the set of SUs; recover the data segment from the at least one ofthe decode threshold number of SUs or the read threshold number of SUsof the set of SUs in accordance with processing the read data request;and transmit, to the another computing device, a read data response thatis based on the processing the read data request.
 2. The computingdevice of claim 1, wherein the processing circuitry is furtherconfigured to execute the operational instructions to: maintain thememory ranking information for the set of SUs within the DSN based onupdating a read ranking number corresponding to a SU of the set of SUsbased on a number of EDSs of the set of EDSs that are received from theSU of the set of SUs that are successfully used to recover the datasegment divided by a total number of corresponding read requests issuedto the SU of the set of SUs.
 3. The computing device of claim 1, whereinthe processing circuitry is further configured to execute theoperational instructions to: select at least one of the decode thresholdnumber of SUs or the read threshold number of SUs of the set of SUs toservice the read data request based on the memory ranking informationfor the set of SUs based on at least one of identifying the readthreshold number of SUs as being associated with highest read rankingnumbers or identifying the read threshold number of SUs as beingassociated with read ranking numbers greater than a minimum rankingthreshold level.
 4. The computing device of claim 1, wherein theprocessing circuitry is further configured to execute the operationalinstructions to: recover the data segment from the at least one of thedecode threshold number of SUs or the read threshold number of SUs ofthe set of SUs in accordance with processing the read data requestincluding to issue a read slice request to the at least one of thedecode threshold number of SUs or the read threshold number of SUs ofthe set of SUs, dispersed error decode at least one of the decodethreshold number of EDSs or the read threshold number of EDSs toreproduce the data segment, and aggregate the data segment with at leastone other data segment to reproduce the data object.
 5. The computingdevice of claim 1, wherein: a write threshold number of EDSs providesfor a successful transfer of the set of EDSs from a first at least onelocation in the DSN to a second at least one location in the DSN; theset of EDSs is of pillar width and includes a pillar number of EDSs;each of the decode threshold number, the read threshold number, and thewrite threshold number is less than the pillar number; and the writethreshold number is greater than or equal to the read threshold numberthat is greater than or equal to the decode threshold number.
 6. Thecomputing device of claim 1, wherein the computing device is located ata first premises that is remotely located from a second premises of atleast one SU of the set of SUs within the DSN.
 7. The computing deviceof claim 1 further comprising: a SU of the set of SUs within the DSN, awireless smart phone, a laptop, a tablet, a personal computers (PC), awork station, or a video game device.
 8. The computing device of claim1, wherein the DSN includes at least one of a wireless communicationsystem, a wire lined communication system, a non-public intranet system,a public internet system, a local area network (LAN), or a wide areanetwork (WAN).
 9. A computing device comprising: an interface configuredto interface and communicate with a dispersed or distributed storagenetwork (DSN); memory that stores operational instructions; andprocessing circuitry operably coupled to the interface and to thememory, wherein the processing circuitry is configured to execute theoperational instructions to: maintain memory ranking information for aset of storage units (SUs) within the DSN based on data accessoperations associated therewith including based on updating a readranking number corresponding to a SU of the set of SUs based on a numberof encoded data slices (EDSs) of a set of EDSs that are received fromthe SU of the set of SUs that are successfully used to recover a datasegment divided by a total number of corresponding read requests issuedto the SU of the set of SUs, wherein a data object is segmented into aplurality of data segments, wherein a data segment of the plurality ofdata segments is dispersed error encoded in accordance with dispersederror encoding parameters to produce a set of EDSs that aredistributedly stored in the set of SUs within the DSN, wherein a decodethreshold number of EDSs are needed to recover the data segment, whereina read threshold number of EDSs provides for reconstruction of the datasegment; receive, from another computing device, a read data request;select at least one of a decode threshold number of SUs or a readthreshold number of SUs of the set of SUs to service the read datarequest based on the memory ranking information for the set of SUs;recover the data segment from the at least one of the decode thresholdnumber of SUs or the read threshold number of SUs of the set of SUs inaccordance with processing the read data request including to issue aread slice request to the at least one of the decode threshold number ofSUs or the read threshold number of SUs of the set of SUs, dispersederror decode at least one of the decode threshold number of EDSs or theread threshold number of EDSs to reproduce the data segment, andaggregate the data segment with at least one other data segment toreproduce the data object; and transmit, to the another computingdevice, a read data response that is based on the processing the readdata request.
 10. The computing device of claim 9, wherein theprocessing circuitry is further configured to execute the operationalinstructions to: select at least one of the decode threshold number ofSUs or the read threshold number of SUs of the set of SUs to service theread data request based on the memory ranking information for the set ofSUs based on at least one of identifying the read threshold number ofSUs as being associated with highest read ranking numbers or identifyingthe read threshold number of SUs as being associated with read rankingnumbers greater than a minimum ranking threshold level.
 11. Thecomputing device of claim 9, wherein: a write threshold number of EDSsprovides for a successful transfer of the set of EDSs from a first atleast one location in the DSN to a second at least one location in theDSN; the set of EDSs is of pillar width and includes a pillar number ofEDSs; each of the decode threshold number, the read threshold number,and the write threshold number is less than the pillar number; and thewrite threshold number is greater than or equal to the read thresholdnumber that is greater than or equal to the decode threshold number. 12.The computing device of claim 9, wherein the computing device is locatedat a first premises that is remotely located from a second premises ofat least one SU of the set of SUs within the DSN.
 13. The computingdevice of claim 9 further comprising: a SU of the set of SUs within theDSN, a wireless smart phone, a laptop, a tablet, a personal computers(PC), a work station, or a video game device.
 14. A method for executionby a computing device, the method comprising: maintain memory rankinginformation for a set of storage units (SUs) within a dispersed ordistributed storage network (DSN) based on data access operationsassociated therewith, wherein a data object is segmented into aplurality of data segments, wherein a data segment of the plurality ofdata segments is dispersed error encoded in accordance with dispersederror encoding parameters to produce a set of encoded data slices (EDSs)that are distributedly stored in the set of SUs within the DSN, whereina decode threshold number of EDSs are needed to recover the datasegment, wherein a read threshold number of EDSs provides forreconstruction of the data segment; receiving, via an interface of thecomputing device that is configured to interface and communicate with adispersed or distributed storage network (DSN) and from anothercomputing device, a read data request; selecting at least one of adecode threshold number of SUs or a read threshold number of SUs of theset of SUs to service the read data request based on the memory rankinginformation for the set of SUs; recovering the data segment from the atleast one of the decode threshold number of SUs or the read thresholdnumber of SUs of the set of SUs in accordance with processing the readdata request; and transmitting, via the interface and to the anothercomputing device, a read data response that is based on the processingthe read data request.
 15. The method of claim 14 further comprising:maintaining the memory ranking information for the set of SUs within theDSN based on updating a read ranking number corresponding to a SU of theset of SUs based on a number of EDSs of the set of EDSs that arereceived from the SU of the set of SUs that are successfully used torecover the data segment divided by a total number of corresponding readrequests issued to the SU of the set of SUs.
 16. The method of claim 14further comprising: selecting at least one of the decode thresholdnumber of SUs or the read threshold number of SUs of the set of SUs toservice the read data request based on the memory ranking informationfor the set of SUs based on at least one of identifying the readthreshold number of SUs as being associated with highest read rankingnumbers or identifying the read threshold number of SUs as beingassociated with read ranking numbers greater than a minimum rankingthreshold level.
 17. The method of claim 14 further comprising:recovering the data segment from the at least one of the decodethreshold number of SUs or the read threshold number of SUs of the setof SUs in accordance with processing the read data request including toissue a read slice request to the at least one of the decode thresholdnumber of SUs or the read threshold number of SUs of the set of SUs,dispersed error decode at least one of the decode threshold number ofEDSs or the read threshold number of EDSs to reproduce the data segment,and aggregate the data segment with at least one other data segment toreproduce the data object.
 18. The method of claim 14, wherein: a writethreshold number of EDSs provides for a successful transfer of the setof EDSs from a first at least one location in the DSN to a second atleast one location in the DSN; the set of EDSs is of pillar width andincludes a pillar number of EDSs; each of the decode threshold number,the read threshold number, and the write threshold number is less thanthe pillar number; and the write threshold number is greater than orequal to the read threshold number that is greater than or equal to thedecode threshold number.
 19. The method of claim 14, wherein thecomputing device includes a SU of the set of SUs within the DSN, awireless smart phone, a laptop, a tablet, a personal computers (PC), awork station, or a video game device.
 20. The method of claim 14,wherein the DSN includes at least one of a wireless communicationsystem, a wire lined communication system, a non-public intranet system,a public internet system, a local area network (LAN), or a wide areanetwork (WAN).